Validation of two informant-based screening instruments for personality disorders in a psychiatric outpatient population
Bibliographic record
Abstract
Purpose: The predictive validity of two informant-based screening instruments for personality disorders (PDs), the Standardized Assessment of Personality (SAP) and a short eight-item version (SAPAS-INF), were studied in 103 Dutch psychiatric outpatients, using the SCID-II as the ‘gold standard’. Methods: All patients and their informants were interviewed separately and independently by different interviewers who were unaware of the results in the other conditions. Results: According to the SCID-II, 66 patients had at least one personality disorder (PD). The SAP correctly classified 72% of all participants in the category PD present/absent. The sensitivity and specificity were 69% and 76%, respectively. The positive and negative predictive values were 84% and 58%. The SAPAS-INF, using a cut-off score of 3, correctly classified 70%; the sensitivity and specificity were 76% and 58%, respectively. The positive and the negative predictive values were 77% and 57%. Conclusion: These results show that the informant-based SAP as well as the shorter informant-based SAPAS-INF are adequate; though rather moderate screening instruments for identifying PD. The SAP and the SAPAS-INF, however, both performed worse than the SAPAS-SR, which is based on the patient’s self-report. Therefore, it is concluded that the SAP or the SAPAS-INF can be used as a satisfactory screening instruments for the presence/absence of PD in those cases where patients themselves are unable to provide the required information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".